CN108563588B - Multi-rate interface design method of active power distribution network real-time simulator based on FPGA - Google Patents

Multi-rate interface design method of active power distribution network real-time simulator based on FPGA Download PDF

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CN108563588B
CN108563588B CN201810221838.1A CN201810221838A CN108563588B CN 108563588 B CN108563588 B CN 108563588B CN 201810221838 A CN201810221838 A CN 201810221838A CN 108563588 B CN108563588 B CN 108563588B
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CN108563588A (en
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李鹏
王智颖
王成山
富晓鹏
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Tianjin University
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Abstract

The method for designing the multi-rate interface of the active power distribution network real-time simulator based on the FPGA comprises the following steps: 1) downloading each subsystem information to a corresponding FPGA, wherein a subsystem m is connected with a subsystem n, and the simulation step length of the subsystem m is integral multiple of the simulation step length of the subsystem n; 2) setting the simulation time t as 0, and starting simulation; 3) the simulation time is advanced by one step length, and t is t + delta t; 4) each subsystem completes simulation calculation and interacts simulation interface data; 5) the subsystem m sends the received simulation interface data to the averaging unit, and the subsystem n sends the received simulation interface data to the interpolation unit; 6) judging whether the physical time reaches t, if so, entering 7), otherwise, entering 7 after the real-time simulator stands by to t); 7) and judging whether the simulation time t reaches the simulation finishing time, if so, finishing the simulation, and otherwise, returning to 3). The multi-rate interface design method effectively improves the simulation speed of the multi-FPGA-based active power distribution network real-time simulator.

Description

Multi-rate interface design method of active power distribution network real-time simulator based on FPGA
Technical Field
The invention relates to a multi-rate interface of a real-time simulator. In particular to a multi-rate interface design method of an active power distribution network real-time simulator based on an FPGA.
Background
Along with the massive access of various power distribution side resources such as distributed power sources, energy storage devices, micro-grids and the like, the organization form and the operation characteristics of the active power distribution network are changed deeply and durably. These changes in the active power distribution network make it have greater differences and challenges in planning design, operational optimization, protection control, simulation analysis, etc. compared to conventional power distribution systems. In the aspect of simulation calculation, the dynamic characteristics of various distributed power supplies, energy storage devices, power electronic devices and other novel devices which are widely connected into an active power distribution system are more complex, the requirements cannot be met by steady-state simulation analysis of the traditional power distribution network, and the operation mechanism and the dynamic characteristics of the active power distribution network need to be deeply known by means of fine transient simulation. On this basis, the analysis and research of the detailed dynamic characteristics of the active power distribution network also need to realize the functional requirements of real-time simulation, and especially, the tests and the tests on various controllers, protection devices, intelligent terminals, novel energy management systems and the like need to be carried out in a hardware-in-the-loop (HIL) environment. Currently, the commercial real-time simulators developed abroad include RTDS, ARENE, hyperrsim, NETOMAC, RT-LAB, etc., all of which use serial processors such as dsp (digital Signal processor), cpu (central Processing unit), PowerPC, etc. as underlying hardware computing resources, and achieve computing power of real-time simulation through parallel computing of a plurality of processors.
The complex network structure and the huge system scale of the active power distribution network provide new challenges for the simulation precision, the calculation speed, the hardware resources and the like of the real-time simulator. In an active power distribution network, a power electronic switch has a high-frequency action characteristic, and a smaller simulation step length is needed for the simulation of the element; the simulation scale of the system is further increased by modeling of controllers of the distributed power supply and the energy storage element, controllers of the power electronic converter and the like, and a large burden is brought to hardware computing resources. The real-time simulator based on the serial processor is limited by the signal processing speed and the physical structure, the real-time simulation computing capacity is limited, and meanwhile, the selection of simulation step length and the numerical stability are limited by the transmission delay of data among a plurality of processors.
The FPGA has a large number of parallel bottom layer structures and distributed memories, and depth parallel calculation can be realized; meanwhile, the processing speed of the digital signal is improved by adopting a pipeline operation mode. The FPGA has rich I/O resources, comprises a full-duplex LVDS channel, a user-defined I/O interface, a high-speed transceiver and the like, and can realize board-level interaction of a large amount of data. With the development of FPGA technology, the integrated high-speed transceiver can realize 14.1Gbps data transmission rate, so that high-speed communication among multiple FPGAs becomes possible, and a solid foundation is laid for real-time simulation of a large-scale active power distribution network.
According to the structural characteristics of the active power distribution network, the resolving scale is reduced through system segmentation and parallel solving, and solving tasks of each segmented subsystem are distributed to a plurality of FPGAs, so that the method is an effective means for improving the computing speed and ensuring the real-time performance of simulation. Considering that each divided subsystem may have dynamic characteristics of different time scales, if the whole system adopts the same simulation step length, the selection of the step length size is limited by the time constant of the fast subsystem, and the real-time performance of the simulation is difficult to ensure. On the other hand, the solving scales and solving difficulty degrees of the subsystems are different, actual solving time is often different, and if a uniform simulation step length is set, the FPGAs can wait for each other until all the FPGAs finish solving tasks, so that time redundancy is caused, and the simulation time is increased. Aiming at different subsystems, the simulation step length suitable for the subsystems is adopted, so that the simulation time of the whole system can be effectively saved, and the real-time simulation requirement is met. Meanwhile, a multi-rate simulation interface adapted to the multi-rate simulation interface is required to realize a multi-rate simulation function.
Disclosure of Invention
The invention aims to solve the technical problem of providing a multi-rate interface design method of an active power distribution network real-time simulator based on an FPGA, which can meet the requirements of a multi-rate real-time simulation algorithm.
The technical scheme adopted by the invention is as follows: a multi-rate interface design method of an active power distribution network real-time simulator based on an FPGA comprises the following steps:
1) in an upper computer of an active power distribution network real-time simulator composed of N FPGA, wherein N>1, an active power distribution system to be simulated is divided into N subsystems after being decoupled by a Berilon circuit model according to topological connection relations and FPGA computing resources, basic parameters of elements of the subsystems are read to form a node conductance matrix of an electrical part of each subsystem and a computing matrix of a control part, relevant information of each subsystem is downloaded into the corresponding FPGA, each subsystem corresponds to one FPGA and is arranged in a descending order according to actual resolving time of each subsystem, the number of each subsystem is 1 to N, and the simulation step length of the ith FPGA is set to be tiThe simulation step length of jth FPGA is tjWherein i is 1,2, …, N, j is i +1, i +2, …, N, and t is satisfiedi＝Mi，jtjWherein M isi，，jSimulation that the simulation step length of the ith FPGA is the jth FPGAM times of true step length, Mi，jTaking a positive integer;
2) defining pairs of subsystems all having a direct connection relation topologically,
Figure BDA0001600224430000021
j is i +1, i +2, …, N, if the subsystem i is directly connected to the subsystem j, the subsystem number i is added to the set phi of slow subsystem numberssIn (2), j is added to the set phi of the fast subsystem numbersfIn (3), the definition number m ∈ φsN is a set phifThe number of the subsystem pair corresponding to m one by one;
3) setting the global simulation step length of the simulator as delta t, wherein the delta t is t1The simulation time is t; defining:
d simulation step length t of mth FPGA in global simulation step length delta tmSimulation interface data required by nth FPGA simulation obtained by internal calculationm，n，dThe number of (t) is Nm，nWherein
Figure BDA0001600224430000022
Simulation interface datam，n，d(t) is represented by { a }p(t)}，p＝(d-1)Nm，n+1，(d-1)Nm，n+2，…，(d-1)Nm，n+Nn，n，ao(t) is emulation interface datam，n，dThe p-th data of (1);
the mth FPGA sends simulation interface Data to the nth FPGA within the global simulation step length delta tm，n(t) is
Figure BDA0001600224430000023
The qth simulation step length tmInternally transmitted emulation interface Datam，n(t) is expressed in the form of { data }m，n，q(t)}，
Figure BDA0001600224430000024
The nth FPGA simulates the e-th simulation step length t in the global simulation step length delta tnM is obtained by inner calculationSimulation interface data required by FPGA simulationn，m，eThe number of (t) is Nn，mWherein
Figure BDA0001600224430000025
Simulation interface datan，m，e(t) is represented by the form { br(t)}，r＝(e-1)Nn，m+1，(e-1)Nn，m+2，…，(e-1)Nn，m+Nn，m，br(t) is emulation interface datan，m，eThe r-th data in (t);
the nth FPGA sends simulation interface Data to the mth FPGA within the global simulation step length delta tn，m(t) is
Figure BDA0001600224430000026
Simulation step length tnInternally transmitted emulation interface Datan，m(t) is expressed in the form of { data }n，m，s(t)}，
Figure BDA0001600224430000027
The whole real-time simulator is driven by a clock clk;
4) initializing a simulator, setting the simulation time t as 0, and starting simulation;
5) the simulation time is advanced by one step length, and t is t + delta t;
Figure BDA0001600224430000031
the mth FPGA completes the simulation by using the data read from the average unit of the mth FPGA
Figure BDA0001600224430000032
After step simulation calculation task, the calculated simulation interface Data ism，n(t) sending to the nth FPGA;
Figure BDA00016002244300000316
the nth FPGA completes the simulation by using the data read from the interpolation unit of the nth FPGA
Figure BDA0001600224430000033
After step simulation calculation task, the calculated simulation interface Data isn，m(t) sending to the mth FPGA;
6)
Figure BDA0001600224430000034
the mth FPGA finishes receiving the simulation interface Data sent by the nth FPGAn，mAfter (t), simulating interface Datan，m(t) sending the average data into an average unit of the device to be processed to obtain average data;
Figure BDA0001600224430000035
the nth FPGA finishes receiving the simulation interface Data sent by the mth FPGAm，nAfter (t), simulating interface Datam，n(t) sending the data into an interpolation unit of the device to process to obtain interpolation data;
7) judging whether the physical time reaches the simulation time t, if so, entering the next step, otherwise, entering the next step after the real-time simulator is standby to the simulation time t;
8) and judging whether the simulation time T reaches the set simulation finishing time T, if so, finishing the simulation, otherwise, returning to the step 3).
The interpolation unit in the step 5) and the step 6) is a random access memory RAMm，n，1、RAMm，n，2、RAMm，n，3And RAMm，n，4Read only memory ROMm，nAnd a first-in first-out queue FIFOm，n，1Form, using emulation interface Datam，nLast N of (t-. DELTA.t)n，mSimulation interface data
Figure BDA0001600224430000036
Data of interface with simulationm，n(t) carrying out
Figure BDA0001600224430000037
Performing linear interpolation operation on the next two points, wherein interpolation data obtained by the interpolation operation of the g time is as follows:
Figure BDA0001600224430000038
wherein
Figure BDA0001600224430000039
The specific implementation mode is as follows: will Datam，n(t) write RAMm，n，1In (1), Datam，nLast N of (t-. DELTA.t)m，nSimulation interface data
Figure BDA00016002244300000310
And Datam，n(t) before
Figure BDA00016002244300000311
Simulation interface datam，n，l(t) } write into RAM sequentiallym，n，2In which
Figure BDA00016002244300000312
Respectively from RAMm，n，1And RAMm，n，2Reading out all the simulation interface data to obtain
Figure BDA00016002244300000313
And
Figure BDA00016002244300000314
computing
Figure BDA00016002244300000315
And writing the obtained result into RAMm，n，3In the process, the
Figure BDA0001600224430000041
Write RAMm，n，4In the ROMm，nData stored therein
Figure BDA0001600224430000042
Is in the format of { XcTherein of
Figure BDA0001600224430000043
XcThe number of each element in the group is equal to Nm，n(ii) a Reading ROMm，nData stored therein
Figure BDA0001600224430000044
Respectively connect the RAMm，n，3And RAMm，n，4In turn, every Nm，nEach data is a set of repeated reads
Figure BDA0001600224430000045
Then, obtain
Figure BDA0001600224430000046
And
Figure BDA0001600224430000047
and (3) calculating:
Figure BDA0001600224430000048
and writing the obtained result into FIFOm，n，1Middle, read FIFOm，n，1To obtain interpolation data.
The averaging unit in the step 5) and the step 6) is a random access memory RAMn，m，5Accumulator, FIFO queuen，m，2，FIFOn，m，3Form, simulating interface Datan，m(t) carrying out
Figure BDA0001600224430000049
And (4) performing secondary average operation, wherein average data obtained by the h-th average operation are as follows:
Figure BDA00016002244300000410
wherein
Figure BDA00016002244300000411
The specific implementation mode is as follows: will Datan，m(t) write FIFOn，m，2In, from FIFOn，m，2In the read Datan，m(t) post write RAMn，m，5，RAMn，m，5The read address addr _ r is:
Figure BDA00016002244300000412
slave RAMn，m，5In which all data are read out to obtain
Figure BDA00016002244300000413
Will be provided with
Figure BDA00016002244300000414
In turn according to each
Figure BDA00016002244300000415
The data are sent to an accumulator for accumulation to obtain
Figure BDA00016002244300000416
Personal DatasumCalculating
Figure BDA00016002244300000417
And writing the obtained result into FIFOn，m，3Middle, read FIFOn，m，3The average data is obtained.
The multi-rate interface design method of the active power distribution network real-time simulator based on the FPGA fully considers the hardware characteristics of the FPGA and the structural characteristics of the active power distribution network, effectively realizes various functional requirements of real-time multi-rate simulation of the active power distribution network by facing a multi-rate simulation algorithm, and lays a foundation for realizing the large-scale active power distribution network real-time simulation based on the FPGA.
Drawings
FIG. 1 is a diagram of an interpolation unit design;
FIG. 2 is a diagram of an averaging unit design;
FIG. 3 is a flow chart of a multi-rate interface design of an active power distribution network real-time simulator based on an FPGA;
FIG. 4 is an active power distribution network real-time simulation platform based on FPGA;
FIG. 5 is an example of a test of an active distribution network including photovoltaic, storage batteries;
FIG. 6 is a detailed structure of a photovoltaic/accumulator unit;
FIG. 7 is a detail of a single stage photovoltaic cell;
FIG. 8 is a DC voltage V of a photovoltaic/accumulator unitPV/Battery,dcA simulation result graph;
FIG. 9 shows the photovoltaic output active power P of the photovoltaic unit 1PV1A simulation result graph;
FIG. 10 shows photovoltaic cell 2 grid-connected point A phase current IPV2,aA simulation result graph;
FIG. 11 shows the grid-connected point A phase voltage V of the photovoltaic unit 2PV2,aAnd (5) a simulation result graph.
Detailed Description
The multi-rate interface design method of the active power distribution network real-time simulator based on the FPGA of the present invention is described in detail below with reference to the embodiments and the accompanying drawings.
The invention discloses a multi-rate interface design method of an active power distribution network real-time simulator based on an FPGA (field programmable gate array), belongs to the field of power system simulation, and is particularly suitable for the field of active power distribution network real-time simulation.
As shown in fig. 3, the method for designing the multi-rate interface of the real-time simulator of the active power distribution network based on the FPGA of the present invention comprises the following steps:
1) in an upper computer of an active power distribution network real-time simulator composed of N FPGA, wherein N>1, an active power distribution system to be simulated is divided into N subsystems after being decoupled by a Berilon circuit model according to topological connection relations and FPGA computing resources, basic parameters of elements of the subsystems are read to form a node conductance matrix of an electrical part of each subsystem and a computing matrix of a control part, relevant information of each subsystem is downloaded into the corresponding FPGA, each subsystem corresponds to one FPGA and is arranged in a descending order according to actual resolving time of each subsystem, the number of each subsystem is 1 to N, and the simulation step length of the ith FPGA is set to be tiThe simulation step length of jth FPGA is tjWherein i is 1,2, …, N, j is i +1, i +2, …, N, and t is satisfiedi＝Mi，jtjWherein M isi，jThe simulation step length of the ith FPGA is M times of that of the jth FPGA, and M isi，jTaking a positive integer;
2) defining pairs of subsystems all having a direct connection relation topologically,
Figure BDA0001600224430000051
j is i +1, i +2, …, N, if the subsystem i is directly connected to the subsystem j, the subsystem number i is added to the set phi of slow subsystem numberssIn (2), j is added to the set phi of the fast subsystem numbersfIn (3), the definition number m ∈ φsN is a set phifThe number of the subsystem pair corresponding to m one by one;
3) setting the global simulation step length of the simulator as delta t, wherein the delta t is t1The simulation time is t; defining:
d simulation step length t of mth FPGA in global simulation step length delta tmSimulation interface data required by nth FPGA simulation obtained by internal calculationm，n，dThe number of (t) is Nm，nWherein
Figure BDA0001600224430000052
The simulation interface data datam, n, d (t) is expressed in the form of { a }p(t)}，p＝(d-1)Nm，n+1，(d-1)Nm，n+2，…，(d-1)Nm，n+Nm，n，ap(t) is emulation interface datam，n，dThe p-th data of (1);
the mth FPGA sends simulation interface Data to the nth FPGA within the global simulation step length delta tm，n(t) is
Figure BDA0001600224430000053
The qth simulation step length tmInternally transmitted emulation interface Datam，n(t) is expressed in the form of { data }m，n，q(t)}，
Figure BDA0001600224430000054
The nth FPGA simulates the e-th simulation step length t in the global simulation step length delta tnSimulation interface data required by mth FPGA simulation obtained by internal calculationn，m，eThe number of (t) is Nn，mWherein
Figure BDA0001600224430000061
Simulation interface datan，m，e(t) is represented by the form { br(t)}，r＝(e-1)Nn，m+1，(e-1)Nn，m+2，…，(e-1)Nn，m+Nn，m，br(t) is emulation interface datan，m，eThe r-th data in (t);
the nth FPGA sends simulation interface Data to the mth FPGA within the global simulation step length delta tn，m(t) is
Figure BDA0001600224430000062
Simulation step length tnInternally transmitted emulation interface Datan，m(t) is expressed in the form of { data }n，m，s(t)}，
Figure BDA0001600224430000063
The whole real-time simulator is driven by a clock clk;
4) initializing a simulator, setting the simulation time t as 0, and starting simulation;
5) the simulation time is advanced by one step length, and t is t + delta t;
Figure BDA0001600224430000064
the mth FPGA completes the simulation by using the data read from the average unit of the mth FPGA
Figure BDA0001600224430000065
After step simulation calculation task, the calculated simulation interface Data ism，n(t) sending to the nth FPGA;
Figure BDA0001600224430000066
nth FPGA utilizes fromThe data required by the simulation read in the interpolation unit of the self completes
Figure BDA0001600224430000067
After step simulation calculation task, the calculated simulation interface Data isn，m(t) sending to the mth FPGA;
6)
Figure BDA0001600224430000068
the mth FPGA finishes receiving the simulation interface Data sent by the nth FPGAn，mAfter (t), simulating interface Datan，m(t) sending the average data into an average unit of the device to be processed to obtain average data;
Figure BDA0001600224430000069
the nth FPGA finishes receiving the simulation interface Data sent by the mth FPGAm，nAfter (t), simulating interface Datam，n(t) sending the data into an interpolation unit of the device to process to obtain interpolation data;
7) judging whether the physical time reaches the simulation time t, if so, entering the next step, otherwise, entering the next step after the real-time simulator is standby to the simulation time t;
8) and judging whether the simulation time T reaches the set simulation finishing time T, if so, finishing the simulation, otherwise, returning to the step 3).
The interpolation units in the above steps 5) and 6) are, as shown in fig. 1, composed of a random access memory RAMm，n，1，RAMm，n，2，RAMm，n，3，RAMm，n，4Read only memory ROMm，nAnd a first-in first-out queue FIFOm，n，1Form, using emulation interface Datam，nLast N of (t-. DELTA.t)n，mSimulation interface data
Figure BDA00016002244300000610
Data of interface with simulationm，n(t) carrying out
Figure BDA00016002244300000611
Performing linear interpolation operation on the next two points, wherein interpolation data obtained by the interpolation operation of the g time is as follows:
Figure BDA0001600224430000071
wherein
Figure BDA0001600224430000072
The specific implementation mode is as follows: will Datam，n(t) write RAMm，n，1In (1), Datam，nLast N of (t-. DELTA.t)m，nSimulation interface data
Figure BDA0001600224430000073
And Datam，n(t) before
Figure BDA0001600224430000074
Simulation interface datam，n，l(t) } write into RAM sequentiallym，n，2In which
Figure BDA0001600224430000075
Respectively from RAMm，n，1And RAMm，n，2Reading out all the simulation interface data to obtain
Figure BDA0001600224430000076
And
Figure BDA0001600224430000077
computing
Figure BDA0001600224430000078
And writing the obtained result into RAMm，n，3In the process, the
Figure BDA0001600224430000079
Write RAMm，n，4In the ROMm，nData stored therein
Figure BDA00016002244300000710
Is in the format of { XcTherein of
Figure BDA00016002244300000711
XcThe number of each element in the group is equal to Nm，n(ii) a Reading ROMm，nData stored therein
Figure BDA00016002244300000712
Respectively connect the RAMm，n，3And RAMm，n，4In turn, every Nm，nEach data is a set of repeated reads
Figure BDA00016002244300000713
Then, obtain
Figure BDA00016002244300000714
And
Figure BDA00016002244300000715
and (3) calculating:
Figure BDA00016002244300000716
and writing the obtained result into FIFOm，n，1Middle, read FIFOm，n，1To obtain interpolation data.
The averaging units described in the above steps 5) and 6), as shown in FIG. 2, are implemented by a RAMn，m，5Accumulator, FIFO queuen，m，2，FIFOn，m，3Form, simulating interface Datan，m(t) carrying out
Figure BDA00016002244300000717
And (4) performing secondary average operation, wherein average data obtained by the h-th average operation are as follows:
Figure BDA00016002244300000718
wherein
Figure BDA00016002244300000719
The specific implementation mode is as follows: will Datan，m(t) write FIFOn，m，2In, from FIFOn，m，2In the read Datan，m(t) post write RAMn，m，5，RAMn，m，5The read address addr _ r is:
Figure BDA00016002244300000720
Figure BDA0001600224430000081
slave RAMn，m，5In which all data are read out to obtain
Figure BDA0001600224430000082
Will be provided with
Figure BDA0001600224430000083
In turn according to each
Figure BDA0001600224430000084
The data are sent to an accumulator for accumulation to obtain
Figure BDA0001600224430000085
Personal DatasumCalculating
Figure BDA0001600224430000086
And writing the obtained result into FIFOn，m，3Middle, read FIFOn，m，3The average data is obtained.
Specific examples are given below:
in the embodiment of the invention, the multi-FPGA-based real-time simulator adopts four Stratix V series FPGA5SGSMD5K2F40C2N of Altera company and matched official development boards thereof to complete the real-time simulation of the active power distribution network containing the photovoltaic power generation system. As shown in FIG. 4, the FPGA1 communicates with the other three FPGAs at the same time, and no data interaction exists among the FPGA2, the FPGA3 and the FPGA 4. And optical fibers are adopted among the development boards to realize communication. The whole real-time simulator is driven by a 125MHz clock, and the single-channel data transmission rate between the FPGAs is 2500 Mbps.
The test example is an IEEE 33 node system including photovoltaic cells and storage batteries, as shown in fig. 5, a photovoltaic/storage battery unit and two single-stage photovoltaic power generation units having the same structure are respectively connected to nodes 18, 22, and 33 of the IEEE 33 node system, the detailed structure of the photovoltaic/storage battery unit is shown in fig. 6, and the detailed structure of the photovoltaic power generation unit is shown in fig. 7. The photovoltaic cell is simulated by a single-diode equivalent circuit, and the storage battery adopts a general equivalent circuit model. In the photovoltaic/storage battery unit, a storage battery is connected with a photovoltaic battery in parallel through a DC/DC converter and a direct current bus, the photovoltaic battery adopts a bipolar form, the DC/DC of the photovoltaic battery is a Boost booster circuit, and the reference value of photovoltaic voltage is set to 750V. The DC/DC in the storage battery pack adopts a bidirectional Boost/Buck circuit, the storage battery is in a Boost circuit mode when discharging, the storage battery is in a Buck voltage reduction circuit mode when charging, the storage battery pack is used for maintaining the constant bus voltage, the reference value of the bus voltage is set to 750V, the inverter adopts PQ control, and the constant output active power and reactive power of the whole hybrid system are maintained. The photovoltaic unit 1 and the photovoltaic unit 2 have the same structural parameters, and the inverter adopts VdcQ control, reactive power reference set to 0 Var. And when the simulation scene is set to be 2.0s, the grid-connected point of the photovoltaic unit 2 has an A-phase grounding short-circuit fault.
The whole calculation example is simulated on a multi-FPGA real-time simulator, wherein an IEEE 33 node system occupies an FPGA1, and three photovoltaic power generation units respectively occupy an FPGA2, an FPGA3 and an FPGA 4. The simulation step lengths of the photovoltaic/storage battery system and the photovoltaic power generation unit are set to be 4 mu s, and the simulation step length of the IEEE 33 node system is set to be 8 mu s.
Simulation results of the real-time simulator based on the FPGA and the commercial software PSCAD/EMTDC are shown in fig. 8 to 11, and the PSCAD/EMTDC uses a single simulation step size of 4 μ s. As can be seen from the figure, the results given by the two simulation systems are basically consistent, so that the correctness and the effectiveness of the design of the multi-rate interface of the active power distribution network real-time simulator based on the FPGA are verified.

Claims (1)

1. A multi-rate interface design method of an active power distribution network real-time simulator based on an FPGA is characterized by comprising the following steps:
1) in an upper computer of an active power distribution network real-time simulator composed of N FPGA, wherein N>1, an active power distribution system to be simulated is divided into N subsystems after being decoupled by a Berilon circuit model according to topological connection relations and FPGA computing resources, basic parameters of elements of the subsystems are read to form a node conductance matrix of an electrical part of each subsystem and a computing matrix of a control part, relevant information of each subsystem is downloaded into the corresponding FPGA, each subsystem corresponds to one FPGA and is arranged in a descending order according to actual resolving time of each subsystem, the number of each subsystem is 1 to N, and the simulation step length of the ith FPGA is set to be tiThe simulation step length of jth FPGA is tjWherein i is 1,2, …, N, j is i +1, i +2, …, N, and t is satisfiedi＝Mi,jtjWherein M isi,jThe simulation step length of the ith FPGA is M times of that of the jth FPGA, and M isi,jTaking a positive integer;
2) defining pairs of subsystems all having a direct connection relation topologically,
Figure FDA00027593338000000112
if the subsystem i is directly connected with the subsystem j, adding the subsystem number i into the set of the slow subsystem numbers
Figure FDA0002759333800000011
In (2), add j to the set of fast subsystem numbers
Figure FDA0002759333800000012
In (1), define the number
Figure FDA0002759333800000013
Number n is set
Figure FDA0002759333800000014
Neutralization ofNumbering the subsystem pairs corresponding to m one to one;
3) setting the global simulation step length of the simulator as delta t, wherein the delta t is t1The simulation time is t; defining:
d simulation step length t of mth FPGA in global simulation step length delta tmSimulation interface data required by nth FPGA simulation obtained by internal calculationm,n,dThe number of (t) is Nm,nWherein
Figure FDA0002759333800000015
Simulation interface datam,n,d(t) is represented by { a }p(t)}，p＝(d-1)Nm,n+1,(d-1)Nm,n+2,…,(d-1)Nm,n+Nm,n，ap(t) is emulation interface datam,n,dThe p-th data of (1);
the mth FPGA sends simulation interface Data to the nth FPGA within the global simulation step length delta tm,n(t) is
Figure FDA0002759333800000016
The qth simulation step length tmInternally transmitted emulation interface Datam,n(t) is expressed in the form of { data }m,n,q(t)}，
Figure FDA0002759333800000017
The nth FPGA simulates the e-th simulation step length t in the global simulation step length delta tnSimulation interface data required by mth FPGA simulation obtained by internal calculationn,m,eThe number of (t) is Nn,mWherein
Figure FDA0002759333800000018
Simulation interface datan,m,e(t) is represented by the form { br(t)}，r＝(e-1)Nn,m+1,(e-1)Nn,m+2,…,(e-1)Nn,m+Nn,m，br(t) is emulation interface datan,m,eThe r-th data in (t);
simulation step length delta t of nth FPGA in global stateSimulation interface Data internally transmitted to mth FPGAn,m(t) is
Figure FDA0002759333800000019
Simulation step length tnInternally transmitted emulation interface Datan,m(t) is expressed in the form of { data }n,m,s(t)}，
Figure FDA00027593338000000110
The whole real-time simulator is driven by a clock clk;
4) initializing a simulator, setting the simulation time t as 0, and starting simulation;
5) the simulation time is advanced by one step length, and t is t + delta t;
Figure FDA00027593338000000111
the mth FPGA completes the simulation by using the data read from the average unit of the mth FPGA
Figure FDA0002759333800000021
After step simulation calculation task, the calculated simulation interface Data ism,n(t) sending to the nth FPGA;
Figure FDA0002759333800000022
the nth FPGA completes the simulation by using the data read from the interpolation unit of the nth FPGA
Figure FDA0002759333800000023
After step simulation calculation task, the calculated simulation interface Data isn,m(t) sending to the mth FPGA;
6)
Figure FDA0002759333800000024
the mth FPGA finishes receiving the simulation interface Data sent by the nth FPGAn,mAfter (t), simulating interface Datan,m(t) feeding into the averagingThe unit processes the data to obtain average data;
Figure FDA0002759333800000025
the nth FPGA finishes receiving the simulation interface Data sent by the mth FPGAm,nAfter (t), simulating interface Datam,n(t) sending the data into an interpolation unit of the device to process to obtain interpolation data;
7) judging whether the physical time reaches the simulation time t, if so, entering the next step, otherwise, entering the next step after the real-time simulator is standby to the simulation time t;
8) judging whether the simulation time T reaches a set simulation finishing time T, if so, finishing the simulation, otherwise, returning to the step 3);
the interpolation unit in the step 5) and the step 6) is a random access memory RAMm,n,1、RAMm,n,2、RAMm,n,3And RAMm,n,4Read only memory ROMm,nAnd a first-in first-out queue FIFOm,n,1Form, using emulation interface Datam,nLast N of (t-. DELTA.t)n,mSimulation interface data
Figure FDA0002759333800000026
Data of interface with simulationm,n(t) carrying out
Figure FDA0002759333800000027
Performing linear interpolation operation on the next two points, wherein interpolation data obtained by the interpolation operation of the g time is as follows:
Figure FDA0002759333800000028
wherein
Figure FDA0002759333800000029
The specific implementation mode is as follows: will Datam,n(t) write RAMm,n,1In (1), Datam,nLast N of (t-. DELTA.t)m,nSimulation interface data
Figure FDA00027593338000000210
And Datam,n(t) before
Figure FDA00027593338000000211
Simulation interface datam,n,l(t) } write into RAM sequentiallym,n,2In which
Figure FDA00027593338000000212
Respectively from RAMm,n,1And RAMm,n,2Reading out all the simulation interface data to obtain
Figure FDA00027593338000000213
And
Figure FDA00027593338000000214
computing
Figure FDA00027593338000000215
And writing the obtained result into RAMm,n,3In the process, the
Figure FDA00027593338000000216
Write RAMm,n,4In the ROMm,nData stored therein
Figure FDA0002759333800000031
Is in the format of { XcTherein of
Figure FDA0002759333800000032
Figure FDA0002759333800000033
XcThe number of each element in the group is equal to Nm,n(ii) a Reading ROMm,nData stored therein
Figure FDA0002759333800000034
Respectively connect the RAMm,n,3And RAMm,n,4In turn, every Nm,nEach data is a set of repeated reads
Figure FDA0002759333800000035
Then, obtain
Figure FDA0002759333800000036
And
Figure FDA0002759333800000037
and (3) calculating:
Figure FDA0002759333800000038
Figure FDA0002759333800000039
and writing the obtained result into FIFOm,n,1Middle, read FIFOm,n,1Obtaining interpolation data from the data in (1);
the averaging unit in the step 5) and the step 6) is a random access memory RAMn,m,5Accumulator, FIFO queuen,m,2，FIFOn,m,3Form, simulating interface Datan,m(t) carrying out
Figure FDA00027593338000000310
And (4) performing secondary average operation, wherein average data obtained by the h-th average operation are as follows:
Figure FDA00027593338000000311
wherein
Figure FDA00027593338000000312
The specific implementation mode is as follows: will Datan,m(t) write FIFOn,m,2In, from FIFOn,m,2In the read Datan,m(t) post write RAMn,m,5，RAMn,m,5The read address addr _ r is:
Figure FDA00027593338000000313
slave RAMn,m,5In which all data are read out to obtain
Figure FDA00027593338000000314
Will be provided with
Figure FDA00027593338000000315
In turn according to each
Figure FDA00027593338000000316
The data are sent to an accumulator for accumulation to obtain
Figure FDA00027593338000000317
Personal DatasumCalculating
Figure FDA00027593338000000318
And writing the obtained result into FIFOn,m,3Middle, read FIFOn,m,3The average data is obtained.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102306078A (en) * 2011-08-09 2012-01-04 河北省电力建设调整试验所 Power grid information three-dimensional display method based on multiple display diagram types
CN103455668A (en) * 2013-08-23 2013-12-18 中国南方电网有限责任公司电网技术研究中心 Electromagnetic transient simulation interpolation method of state variable oriented nodal analysis combination frame
CN104537233A (en) * 2014-12-23 2015-04-22 国家电网公司 Distribution network pseudo measurement generating method based on kernel density estimation
CN104715103A (en) * 2015-01-12 2015-06-17 国家电网公司 Photovoltaic cell real-time simulation model design method based on FPGA

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030182639A1 (en) * 2002-03-25 2003-09-25 International Business Machines Corporation Circuit simulator system and method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102306078A (en) * 2011-08-09 2012-01-04 河北省电力建设调整试验所 Power grid information three-dimensional display method based on multiple display diagram types
CN103455668A (en) * 2013-08-23 2013-12-18 中国南方电网有限责任公司电网技术研究中心 Electromagnetic transient simulation interpolation method of state variable oriented nodal analysis combination frame
CN104537233A (en) * 2014-12-23 2015-04-22 国家电网公司 Distribution network pseudo measurement generating method based on kernel density estimation
CN104715103A (en) * 2015-01-12 2015-06-17 国家电网公司 Photovoltaic cell real-time simulation model design method based on FPGA

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Synchronisation mechanism and interfaces design of multi-FPGA-based real-time simulator for microgrids;Peng Li等;《The Institution of Engineering and Technology 2017》;20171231;第11卷(第12期);3088-3096 *
基于RTDS的有源配电网暂态实时仿真与分析;于力;《电力系统及其自动化学报》;20150430;第27卷(第4期);18-25 *

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